Application effect of short-term traffic flow prediction method based on CNNBLSTM algorithm. by Guozhu Sui, Meixia Song, Ke Bian, Mingzhen Zhang, Xiaogang Zhang, Yiru Wang

“…Reduced forecast efficiency and accuracy are the result of traditional traffic flow prediction algorithms' inability to adequately capture the spatiotemporal characteristics and dynamic changes of traffic flow. …”
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A novel methodological approach to SaaS churn prediction using whale optimization algorithm. by Muhammed Kotan, Ömer Faruk Seymen, Levent Çallı, Sena Kasım, Burcu Çarklı Yavuz, Tijen Över Özçelik

“…This study introduces a novel approach to SaaS churn prediction using the Whale Optimization Algorithm (WOA) for feature selection. …”
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Deep learning for algorithmic trading: A systematic review of predictive models and optimization strategies by MD Shahriar Mahmud Bhuiyan, MD AL Rafi, Gourab Nicholas Rodrigues, MD Nazmul Hossain Mir, Adit Ishraq, M.F. Mridha, Jungpil Shin

Subjects: “…Algorithmic trading…”
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A Machine Learning Algorithm to Predict Medical Device Recall by the Food and Drug Administration by Victor Barbosa Slivinskis, Isabela Agi Maluli, Joshua Seth Broder

“…Our objective was to evaluate the sensitivity, specificity, and accuracy of a machine learning (ML) algorithm using publicly available data to predict medical device recalls by the FDA. …”
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Predicting carbon dioxide emissions using deep learning and Ninja metaheuristic optimization algorithm by Anis Ben Ghorbal, Azedine Grine, Ibrahim Elbatal, Ehab M. Almetwally, Marwa M. Eid, El-Sayed M. El-Kenawy

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Educational resources recommendation algorithm based on GMF-MLP-NeuMF prediction model by Rui Wang, Qiusheng Cui, Yezhi Xiao, Jinfeng Du, Ruicheng Yue

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Explainable machine learning algorithm to predict cardiovascular event in patients undergoing peritoneal dialysis by Qiqi Yan, Guiling Liu, Ruifeng Wang, Dandan Li, Xiaoli Chen, Jingjing Cong, Deguang Wang

“…Abstract Objective To compare the performance of predictive models for cardiovascular event (CVE) in patients undergoing peritoneal dialysis (PD) based on machine learning algorithm and Cox proportional hazard regression. …”
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Stacking modeling with genetic algorithm-based hyperparameter tuning for uniaxial compressive strength prediction by Tanveer Alam Munshi, Khanum Popi, Labiba Nusrat Jahan, M. Farhad Howladar, Mahamudul Hashan

“…Additionally, a hybrid stacking model that combines these algorithms was developed. Hyperparameter optimization was conducted using grid search and genetic algorithm. …”
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Research on Coal Structure Prediction Method Based on Genetic Algorithm–BP Neural Network by Cunwu Wang, Xiaobo Peng, Gang Han, Yan Zhao, Yihao Zhu, Ming Zhao

“…This paper proposes a coal structure prediction technology based on deep learning, which uses logging data to achieve single-well prediction of the coal structure. …”
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HYBRID NO-LOSS IMAGE COMPRESSION ALGORITHM BASED ON DISCRETE WAVELET TRANSFORMATION WITH ADAPTIVE PREDICTION by A. A. Boriskevich, L. A. Ruiz

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Retracted: Wearable Power Assistant Robot Sensor Signal Prediction Algorithm and Controller Design by Applied Bionics and Biomechanics

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A multi-site study of clinician perspectives in the lifecycle of an algorithmic risk prediction tool by Rita Dexter, Kristin Kostick-Quenet, Jennifer Blumenthal-Barby

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SMOTE algorithm optimization and application in corporate credit risk prediction with diversification strategy consideration by Han Wei

“…Abstract Against the backdrop of dynamic transformations in the financial sector and prominent corporate diversification trends, credit risk prediction becomes significantly more challenging. On one hand, this study focuses on optimizing the Synthetic Minority Over-Sampling Technique (SMOTE) algorithm for corporate credit risk prediction, thereby enhancing financial institutions’ risk management capabilities. …”
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Analytical Predictive Guidance Algorithm Based on Single Ballistic Coefficient Switching for Mars Aerocapture by Yu-ming Peng, Bo Xu, Xi Lu, Bao-dong Fang, Heng Zhang

“…An aerocapture analytical predictive guidance algorithm for single ballistic coefficient switching is proposed. …”
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Predicting the Matching Possibility of Online Dating Youths Using Novel Machine Learning Algorithm by Karthikeyan Palanisamy, Muthumani Muralidharan

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Reversible data hiding algorithm in encrypted images based on prediction error and bitplane coding by Haiyong WANG, Mengning JI

“…With the increasing use of cloud backup methods for storing important files, the demand for privacy protection has also grown.Reversible data hiding in encrypted images (RDHEI) is an important technology in the field of information security that allows embedding secret information in encrypted images while ensuring error-free extraction of the secret information and lossless recovery of the original plaintext image.This technology not only enhances image security but also enables efficient transmission of sensitive information over networks.Its application in cloud environments for user privacy protection has attracted significant attention from researchers.A reversible data hiding method in encrypted images based on prediction error and bitplane coding was proposed to improve the embedding rate of existing RDHEI algorithms.Different encoding methods were employed by the algorithm depending on the distribution of the bitplanes, resulting in the creation of additional space in the image.The image was rearranged to allocate the freed-up space to the lower-order planes.Following this, a random matrix was generated using a key to encrypt the image, ensuring image security.Finally, the information was embedded into the reserved space.The information can be extracted and the image recovered by the receiver using different keys.The proposed algorithm achieves a higher embedding rate compared to five state-of-the-art RDHEI algorithms.The average embedding rates on BOWS-2, BOSSBase, and UCID datasets are 3.769 bit/pixel, 3.874 bit/pixel, and 3.148 bit/pixel respectively, which represent an improvement of 12.5%, 6.9% and 8.6% compared to the best-performing algorithms in the same category.Experimental results demonstrate that the proposed algorithm effectively utilizes the redundancy of images and significantly improves the embedding rate.…”
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Refinement of an Algorithm to Detect and Predict Freezing of Gait in Parkinson Disease Using Wearable Sensors by Allison M. Haussler, Lauren E. Tueth, David S. May, Gammon M. Earhart, Pietro Mazzoni

“…The purpose of this paper is to explore how the existing pFOG algorithm can be refined to improve the detection and prediction of FOG. …”
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SOC and SOH Prediction of Lithium‐Ion Batteries Based on LSTM–AUKF Joint Algorithm by Yancheng Song, Jiaqi Lu, Huai Zhang, Guangjun Liu

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Prediction of Sonic Log Values Using a Gradient Boosting Algorithm in the 'AB' Field by Rasif Nahari, Utama Widya, Ardhya Garini Sherly, Fitri Indriani Rista, Pratama Novian Putra Dhea

“…To address missing data, machine learning algorithms, like gradient boosting, provide an effective solution. …”
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Residential Building Energy Usage Prediction Using Bayesian-Based Optimized XGBoost Algorithm by Nabaa Riyadh Baqer, Parviz Rashidi-Khazaee

“…Therefore, engineers and designers try to find a reliable tool to help them analyze and predict the energy consumption of buildings in the early design stages before construction. …”
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